





# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase_        =							{
    '''configuration_xmod''': [
        '''XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''XmodConfig''',
        '''XmodOnnxConfig''',
    ],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase_        =							[
	    '''XMOD_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''XmodForCausalLM''',
	    '''XmodForMaskedLM''',
	    '''XmodForMultipleChoice''',
	    '''XmodForQuestionAnswering''',
	    '''XmodForSequenceClassification''',
	    '''XmodForTokenClassification''',
	    '''XmodModel''',
	    '''XmodPreTrainedModel''',
	]

if TYPE_CHECKING:
	from .configuration_xmod import XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP, XmodConfig, XmodOnnxConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_xmod import (
		    XMOD_PRETRAINED_MODEL_ARCHIVE_LIST,
		    XmodForCausalLM,
		    XmodForMaskedLM,
		    XmodForMultipleChoice,
		    XmodForQuestionAnswering,
		    XmodForSequenceClassification,
		    XmodForTokenClassification,
		    XmodModel,
		    XmodPreTrainedModel,
		)

else:
	import sys

	lowerCAmelCase_        =							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


from __future__ import annotations







def 							A__       (    lowerCamelCase    )	->						int:
				UpperCamelCase_:				Optional[Any]						=    len(lowerCamelCase    ) // 2

				# choose the middle 3 elements
				UpperCamelCase_:				Tuple						=    lst[m - 1 : m + 2]

				# if middle element is peak
				if three[1] > three[0] and three[1] > three[2]:
								return three[1]

				# if increasing, recurse on right
				elif three[0] < three[2]:
								if len(lst[:m]    ) == 2:
												m -= 1
								return peak(lst[m:]    )

				# decreasing
				else:
								if len(lst[:m]    ) == 2:
												m += 1
								return peak(lst[:m]    )


if __name__ == "__main__":
							import doctest

							doctest.testmod()






